similar to: New version (2.2) of the sm package

Dear R helpers, I need to find out maximized log likelihoods, parameters estimates and standard errors (in parentheses) of r largest-order statistics model, with different values of r by using the function rlarg.fit. I want to specify required number of order statistics to the model. I attached my data file with this mail.please help me. Ruposh --- r-help-request at stat.math.ethz.ch wrote:

I am working with a model that I have to estimate a nonparametric function. The model is partial linear i.e. Y=X$\beta$ + f(z) + $\epsilon$ I am using the ' double residual methods' Robinson (1988) Speckman (1988) where I estimate a nonparametric function for each of the parametric variables in terms of the nonparametric one i.e. X[,i]=g(Z)+ u this is done because I need the $E(

Hi There I have a lm object with 4 parameters and I want to test wether 2 parameters are equal using a Wald test (basically b1=b2 or b1-b2 =0). In the help file from R it says that under ANOVA the optional arguments " Terms" or "L" test whether a linear combination is equal to 0. I tried; >anova(m1, Terms = Beta1-Beta2=0) but I get the error: Object " Beta1"

# Your mailer is set to "none" (default on Windows), # hence we cannot send the bug report directly from R. # Please copy the bug report (after finishing it) to # your favorite email program and send it to # # r-bugs@r-project.org # ###################################################### Today I have installed R 1.02.1 on my MSW-95 laptop; it essentially worked, but thre are two

Hi, I'm using R 1001 for Windows NT and the sm library. I'm trying to create plots for my data set like Bowman and Azzalini have in Figure 1.8 (p. 9) of their book for my data (i.e. a contour plot for each group in my data set and its all plotted on 1 plot). The problem I'm having is that R is not drawing closed contour lines for each group. Sometimes it does; other times it

AA> In 2008, I have spotted some errors in a package, one which is AA> likely to have many users (I am not one myself). The more serious AA> errors are in the documentation, since they lead to a completely AA> distorted interpretation of the outcome; in addition, there is (at AA> least) one programming error which produces some wrong AA> computations. A few weeks later, the

Dear R-help list members, I have created a package 'mnormt' with facilities for the multivariate normal and t distributions. The core part is simply an interface to Fortran routines by Alan Genz for computing the integral of two densities over rectangular regions, using an adaptive integration method. Other R functions compute densities and generate random numbers. The starting

There seems to exist peculiar cases where optim does not take care of constraints on the parameters to be optimized over. The call to optim is of the form opt <- optim(cp, fn=sn.dev, gr=sn.dev.gh, method="L-BFGS-B", lower=c(-Inf, 1e-10, -0.99527), upper=c( Inf, Inf, 0.99527), control=control, X=X, y=y, hessian=FALSE) The code has worked fine

Dear List-members, to download a file from the net, the function download.file(..) does the job. However, before embarking on the download, I would like to find out how large the file is. Is there a way to know it? Most easily, this question has been asked before, but I am new to the list. Regards, with thanks in advance, Adelchi Azzalini ---- Adelchi Azzalini <azzalini at

In the document "R Data Import/Export", section "Output to connections", there is the following portion of code: ## convert decimal point to comma in output, using a pipe (Unix) zz <- pipe(paste("sed s/\\./,/ >", "outfile"), "w") cat(format(round(rnorm(100), 4)), sep = "\n", file = zz) close(zz) ## now look at the output

The rpanel package builds on the tcltk package to provide simple interactive controls for R functions, in particular to provide simple forms of dynamic graphics. The intention is to make this form of control particularly easy for R users to implement, with full documentation. The necessary tcltk variables are managed behind the scenes so that users need not be concerned with any

Has Bowman and Azzalini's sm library been ported to R yet (goes with Appied smoothing techniques for data analysis book)? I had a quick go but got tied up at a silly stage of ignorance caused I think (?hope) because I have never seriously used S+ at all. Rather than waste time, perhaps some kind soul has already done it. \John

Dear Prof Azzalini, You have an interesting example of recursive use of uniroot(). [re-cited at the end] However, note that R currently has the same problem as S-plus: Uniroot() doesn't work reliably, recursively. When you found it to be better, you were just lucky. The relevant file in R's source, src/main/optimize.c says /* WARNING : As things stand, these routines should

The package "sm" was obtained twice, one using R's built-in updating of packages, the second directly. In both cases the USA-NC CRAN mirror was used. In both cases, loading the package under R 2.10.1 for Windows resulted in a 'package obsolete' kind of message. Switching the mirror to USA-CA-1 (Berkeley) got a good package that loaded without complaint. R version 2.10.1

Hi all (again), many thanks for the answer to the optimization problem. All is fine now. The problem now is with kernel estimators in sm. package. I do all the work and the graphics good, but I need the density function data for each point, and I don't know how to get it. The only thing I get is the table at the end of the following sequence: >

Hello, I am a newbie to R and the subject of density estimation in two dimensions or more. I would like to have some advice concerning a comparison between the R packages for density estimation in bivariate or higher order problems; I mean explicitly the packages: 1) ash 2) KernSmooth 3) locfit 4) sm. My specific problem now is having a set of numerical pairs (x_i, y_i), arising from a

If I define this function R> ask <- function (message = "Type in datum") eval(parse(prompt = paste(message, ": ", sep = ""))) the following is produced as expected on a Linux/debian machine R> ask("input") input: 3 [1] 3 R> ask("input") input: 3:6 [1] 3 4 5 6 R> ask("input") input: c(3,6) [1] 3 6 If I

Dear all, Does anybody know how to get more evaluation points in performing Nonparametric analysis of repeated measurements data with "sm" library. The following command gives the estimation for 50 points, by I would like to increase to 100 points But I do not know how to do that. library(sm) provide.data(citrate, options=list(describe=FALSE)) provide.data(dogs,

Hi, there: It's my first time to post question in this forum, so thanks for your tolerance if my question is too naive. I am using a nonparametric smoothing procedure in sm package to generate smoothed survival curves for continuous covariate. I want to truncate the suvival curve and only display the part with covariate value between 0 and 7. The following is the code I wrote:

On 17/11/2017 10:47 AM, Adelchi Azzalini wrote: > Since I have updated my Linux system, and consequently re-installed R, I > am unable to see HTML documentation which I used to access via a web > browser. To be more specific, my R installation is declared to be here: > > > R RHOME > /usr/local/lib/R > > However, if I look at a location such as >